Motion-induced dose artifacts in helical tomotherapy
Bibliographic record
Abstract
Tumor motion is a particular concern for a complex treatment modality such as helical tomotherapy, where couch position, gantry rotation and MLC leaf opening all change with time. In the present study, we have investigated the impact of tumor motion for helical tomotherapy, which could result in three distinct motion-induced dose artifacts, namely (1) dose rounding, (2) dose rippling and (3) IMRT leaf opening asynchronization effect. Dose rounding and dose rippling effects have been previously described, while the IMRT leaf opening asynchronization effect is a newly discovered motion-induced dose artifact. Dose rounding is the penumbral widening of a delivered dose distribution near the edges of a target volume along the direction of tumor motion. Dose rippling is a series of periodic dose peaks and valleys observed within the target region along the direction of couch motion, due to an asynchronous interplay between the couch motion and the longitudinal component of tumor motion. The IMRT leaf opening asynchronization effect is caused by an asynchronous interplay between the temporal patterns of leaf openings and tumor motion. The characteristics of each dose artifact were investigated individually as functions of target motion amplitude and period for both non-IMRT and IMRT helical tomotherapy cases, through computer simulation modeling and experimental verification. The longitudinal dose profiles generated by the simulation program agreed with the experimental data within +/-0.5% and +/-1.5% inside the PTV region for the non-IMRT and IMRT cases, respectively. The dose rounding effect produced a penumbral increase up to 20.5 mm for peak-to-peak target motion amplitudes ranging from 1.0 cm to 5.0 cm. Maximum dose rippling magnitude of 25% was calculated, when the target motion period approached an unusually high value of 10 s. The IMRT leaf opening asynchronization effect produced dose differences ranging from -29% to 7% inside the PTV region. This information on the potential motion-induced dose artifacts will be important in defining the optimal motion mitigation strategies for lung tomotherapy.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".